Team Lead Data & AI Engineering (m/f/d)
At Statista, we're all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well...
At Statista, we're all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions.
Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees.
We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters - keep writing it as part of our team.
Are you ready to join us?
Your Mission
Lead, grow, and enable a high-performing team of Data and AI Engineers that builds the next generation of automation and AI solutions for the company. You will set direction, create a culture of excellence and collaboration, and ensure your team delivers reliable, scalable AI systems that matter to the business.
Your Tasks
- Lead, coach, and develop a team of Data and AI Engineers, setting clear goals, running effective 1:1s, and supporting their career growth.
- Provide technical leadership and guidance: review code, shape architecture decisions, and ensure high engineering standards across the team.
- Drive the end-to-end delivery of advanced Data and AI-powered solutions, coordinating priorities, timelines, and resources across your team.
- Design, deploy, and oversee scalable cloud infrastructure for AI services and APIs, ensuring reliability, performance, and cost efficiency.
- Identify and prioritize automation opportunities with stakeholders, then guide your team to implement solutions that streamline workflows company-wide.
- Act as the primary point of contact for your area, aligning with product, data, and business leaders to ensure your team focuses on high-impact work.
- Champion modern AI and automation practices within the team, creating space for experimentation, learning, and adoption of state-of-the-art tools.
Your Profile
- 5+ years of experience in Data Engineering, Data Operations, or Software Engineering, including proven experience leading and developing technical teams.
- Strong hands-on Python skills in building scalable data pipelines, automation, and backend services, plus the ability to guide others in these areas.
- Experience leading teams that operate on cloud infrastructure (AWS preferred: ECS, EC2, EKS, S3, Lambda), workflow orchestration (Apache Airflow), containerization (Docker), and version control (git).
- Deep understanding of AI principles: foundation models, retrieval-augmented generation (RAG), prompt engineering, evaluation metrics, and how to guide a team in choosing the right approach.
- Excellent English communication skills, with a track record of leading cross-functional initiatives, aligning stakeholders, and influencing technical decisions.
- Passion for people leadership and innovation, with energy for building autonomous AI tools, agent networks, and scalable AI solutions in a high-growth environment.
What we offer
In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work! Join us and benefit from:
- Work from abroad up to 30 calendar days a year
- Hybrid work and flex-time
- International team and social events
- Subsidized urban mobility and access to fitness and wellness options
- Free access to Langdock and all its amazing functionalities
- Career & training opportunities
- Attractive locations and modern offices
- Mental health support with OpenUp
Some of the benefits listed here apply only to the German entity and to Junior-level roles or above.
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